Prediction of cancer incidence in Tyrol/Austria for year of diagnosis 2020

Summary

Background

Prediction of the number of incident cancer cases is very relevant for health planning purposes and allocation of resources. The shift towards elder age groups in central European populations in the next decades is likely to contribute to an increase in cancer incidence for many cancer sites. In Tyrol, cancer incidence data have been registered on a high level of completeness for more than 20 years. We therefore aimed to compute well-founded predictions of cancer incidence for Tyrol for the year 2020 for all frequent cancer sites and for all cancer sites combined.

Methods

After defining a prediction base range for every cancer site, we extrapolated the age-specific time trends in the prediction base range following a linear model for increasing and a log-linear model for decreasing time trends. The extrapolated time trends were evaluated for the year 2020 applying population figures supplied by Statistics Austria.

Results

Compared with the number of annual incident cases for the year 2009 for all cancer sites combined except non-melanoma skin cancer, we predicted an increase of 235 (15 %) and 362 (21 %) for females and males, respectively. For both sexes, more than 90 % of the increase is attributable to the shift toward older age groups in the next decade. The biggest increase in absolute numbers is seen for females in breast cancer (92, 21 %), lung cancer (64, 52 %), colorectal cancer (40, 24 %), melanoma (38, 30 %) and the haematopoietic system (37, 35 %) and for males in prostate cancer (105, 25 %), colorectal cancer (91, 45 %), the haematopoietic system (71, 55 %), bladder cancer (69, 100 %) and melanoma (64, 52 %).

Conclusions

The increase in the number of incident cancer cases of 15 % in females and 21 % in males in the next decade is very relevant for planning purposes. However, external factors cause uncertainty in the prediction of some cancer sites (mainly prostate cancer and colorectal cancer) and the prediction intervals are still broad. Therefore, our predictions must be interpreted with some caution.